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Sparsified federated learning with differential privacy for intrusion detection in VANETs based on Fisher Information Matrix

https://doi.org/10.1371/journal.pone.0301897

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-59410-7_33openalex-snapshot

FedSel: Federated SGD Under Local Differential Privacy with Top-k Dimension Selection

inferredcites →https://doi.org/10.1007/978-3-319-66402-6_27openalex-snapshot

Analyzing the Capabilities of the CAN Attacker

inferredcites →https://doi.org/10.1016/j.amc.2023.128489openalex-snapshot

Fisher information and shape-morphing modes for solving the Fokker–Planck equation in higher dimensions

inferredcites →https://doi.org/10.1109/comst.2022.3149714openalex-snapshot

A Survey of Collaborative Machine Learning Using 5G Vehicular Communications

inferredcites →https://doi.org/10.1109/comst.2022.3178081openalex-snapshot

Survey on Issues and Recent Advances in Vehicular Public-Key Infrastructure (VPKI)

inferredcites →https://doi.org/10.1109/comst.2023.3309864openalex-snapshot

Intrusion Detection in the Automotive Domain: A Comprehensive Review

inferredcites →https://doi.org/10.1109/dsaa.2016.20openalex-snapshot

Anomaly Detection in Automobile Control Network Data with Long Short-Term Memory Networks

inferredcites →https://doi.org/10.1109/focs.2013.53openalex-snapshot

Local Privacy and Statistical Minimax Rates

inferredcites →https://doi.org/10.1109/icde.2016.7498248openalex-snapshot

Private spatial data aggregation in the local setting

inferredcites →https://doi.org/10.1109/ivs.2016.7535434openalex-snapshot

Visible Light inter-vehicle Communication for platooning of autonomous vehicles

inferredcites →https://doi.org/10.1109/jiot.2020.3037194openalex-snapshot

Local Differential Privacy-Based Federated Learning for Internet of Things

inferredcites →https://doi.org/10.1109/jiot.2021.3084796openalex-snapshot

MTH-IDS: A Multitiered Hybrid Intrusion Detection System for Internet of Vehicles

inferredcites →https://doi.org/10.1109/jiot.2023.3290818openalex-snapshot

QuAsyncFL: Asynchronous Federated Learning With Quantization for Cloud–Edge–Terminal Collaboration Enabled AIoT

inferredcites →https://doi.org/10.1109/jsac.2023.3242710openalex-snapshot

Communication-Efficient Distributed Learning: An Overview

inferredcites →https://doi.org/10.1109/pst.2017.00017openalex-snapshot

OTIDS: A Novel Intrusion Detection System for In-vehicle Network by Using Remote Frame

inferredcites →https://doi.org/10.1109/secon55815.2022.9918586openalex-snapshot

FedMix: A Sybil Attack Detection System Considering Cross-layer Information Fusion and Privacy Protection

inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot

Membership Inference Attacks Against Machine Learning Models

inferredcites →https://doi.org/10.1109/srds51746.2020.00026openalex-snapshot

On the Detection of Shilling Attacks in Federated Collaborative Filtering

inferredcites →https://doi.org/10.1109/tifs.2018.2870826openalex-snapshot

READ: Reverse Engineering of Automotive Data Frames

inferredcites →https://doi.org/10.1109/tifs.2020.2988575openalex-snapshot

Federated Learning With Differential Privacy: Algorithms and Performance Analysis

inferredcites →https://doi.org/10.1109/tifs.2023.3309095openalex-snapshot

Privacy-Encoded Federated Learning Against Gradient-Based Data Reconstruction Attacks

inferredcites →https://doi.org/10.1109/tii.2022.3161517openalex-snapshot

Boosting Accuracy of Differentially Private Federated Learning in Industrial IoT With Sparse Responses

inferredcites →https://doi.org/10.1109/tits.2020.2988065openalex-snapshot

A Probabilistic Data Structures-Based Anomaly Detection Scheme for Software-Defined Internet of Vehicles

inferredcites →https://doi.org/10.1109/tits.2020.3017882openalex-snapshot

Novel Deep Learning-Enabled LSTM Autoencoder Architecture for Discovering Anomalous Events From Intelligent Transportation Systems

inferredcites →https://doi.org/10.1109/tits.2021.3055351openalex-snapshot

Threat Analysis for Automotive CAN Networks: A GAN Model-Based Intrusion Detection Technique

inferredcites →https://doi.org/10.1109/tits.2022.3202869openalex-snapshot

Two-Stage Intrusion Detection System in Intelligent Transportation Systems Using Rule Extraction Methods From Deep Neural Networks

inferredcites →https://doi.org/10.1109/tmi.2023.3239391openalex-snapshot

Do Gradient Inversion Attacks Make Federated Learning Unsafe?

inferredcites →https://doi.org/10.1109/tnet.2023.3317870openalex-snapshot

Shield Against Gradient Leakage Attacks: Adaptive Privacy-Preserving Federated Learning

inferredcites →https://doi.org/10.1109/tvt.2020.2984878openalex-snapshot

Simulation Framework for Misbehavior Detection in Vehicular Networks

inferredcites →https://doi.org/10.1145/2660267.2660348openalex-snapshot

RAPPOR

inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot

Deep Learning with Differential Privacy

inferredcites →https://doi.org/10.1145/3489517.3530469openalex-snapshot

SS-LRU

inferredcites →https://doi.org/10.1145/3570954openalex-snapshot

AI-Based Intrusion Detection Systems for In-Vehicle Networks: A Survey

inferredcites →https://doi.org/10.1371/journal.pone.0155781openalex-snapshot

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security

inferredcites →https://doi.org/10.1561/9781601988195openalex-snapshot

The Algorithmic Foundations of Differential Privacy

inferredcites →https://doi.org/10.1631/fitee.1700813openalex-snapshot

Artificial intelligence and statistics

inferredcites →https://doi.org/10.48550/arxiv.1805.10559openalex-snapshot

cpSGD: Communication-efficient and differentially-private distributed SGD

inferredcites →https://doi.org/10.48550/arxiv.2306.06062openalex-snapshot

Neural FIM for learning Fisher Information Metrics from point cloud data

inferredcites →https://doi.org/10.5220/0006639801080116openalex-snapshot

Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.2626508openalex-extracted

Entry Limiting Agreements for Pharmaceuticals: Pay-for-Delay and Authorized Generic Deals

inferred← citeshttps://doi.org/10.1002/dac.70305openalex-snapshot

Enhancing VANET Security Through ANFIS‐Based Intrusion Detection and Element Perturbation

inferred← citeshttps://doi.org/10.1002/ett.70280openalex-snapshot

Development of Hybrid Explainable Artificial Intelligence With Swin Vision Transformer Intrusion Detection for Securing VANETs From Attacks

inferred← citeshttps://doi.org/10.1002/ett.70311openalex-snapshot

Edge‐Driven Federated Learning Approach for Distributed Assault Monitoring in Vehicular Networks

inferred← citeshttps://doi.org/10.1016/j.adhoc.2025.104031openalex-snapshot

Generative AI-based intrusion detection systems for intra-vehicle networks

inferred← citeshttps://doi.org/10.1016/j.dajour.2025.100641openalex-snapshot

An adaptive framework for privacy-preserving analytics in federated intrusion detection

inferred← citeshttps://doi.org/10.1016/j.ins.2026.124212openalex-snapshot

Taylor-sparsified differentially private federated learning with support-consensus robust aggregation

inferred← citeshttps://doi.org/10.1016/j.iot.2025.101730openalex-snapshot

Federated learning for sustainable intrusion detection systems: A review of green computing strategies and future directions

inferred← citeshttps://doi.org/10.1049/itr2.70182openalex-snapshot

An Efficient Intrusion Detection System Using Domain‐Aware Meta‐Learning with Adapter‐Based Few‐Shot Adaptation in Vehicular Ad‐Hoc Networks (VANETs)

inferred← citeshttps://doi.org/10.1109/commantel68363.2025.11368347openalex-snapshot

Privacy-Preserving Intrusion Detection Using Federated Learning and Differential-Privacy-Inspired Noise

inferred← citeshttps://doi.org/10.1109/jiot.2024.3521609openalex-snapshot

CLDP=FATD: Secure Federated Averaging Threat Detection Framework for Intelligent Vehicle Sensor Networks Based on Client-Level Differential Privacy

inferred← citeshttps://doi.org/10.1155/int/8810907openalex-snapshot

Trustworthy Distributed Load Forecasting in Resource‐Limited Smart Grids and Buildings via Random Layer Aggregation

inferred← citeshttps://doi.org/10.1371/journal.pone.0315716openalex-snapshot

Road side unit deployment optimization for the reliability of internet of vehicles based on information transmission model

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